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The following topics are addressed: mission operations support; planning and scheduling; fault isolation/diagnosis; image processing and machine vision; data management; and modeling and simulation.
This publication comprises the papers presented at the 1988 Goddard Conference on Space Applications of Artificial Intelligence held at the NASA/Goddard Space Flight Center, Greenbelt, Maryland on May 24, 1988. The purpose of this annual conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed. The papers in these proceedings fall into the following areas: mission operations support, planning and scheduling; fault isolation/diagnosis; image processing and machine vision; data management; modeling and simulation; and development tools methodologies.
NASA's Johnson Space Center (JSC) has created the specifications for a new kind of image processing machine, a video-rate coordinate remapper. Previous image-processing machines for machine vision typically have done point operations without changing the geometry of the image. The JSC Programmable Remapper offers complete flexibility in changing the coordinates of an input image at video rates. Presented here are the main capabilities and some of the applications of such a device.
Visual sensor responses may be used to classify objects on the basis of their surface reflectance functions. In a color image, the image data are represented as a vector of sensor responses at each point in the image. This vector depends both on the surface reflectance functions and on the spectral power distribution of the ambient illumination. Algorithms designed to classify objects on the basis of their surface reflectance functions typically attempt to overcome the dependence of the sensor responses on the illuminant by integrating sensor data collected from multiple surfaces. In machine vision applications, it is shown that it is often possible to design the sensor spectral responsivities so that the vector direction of the sensor responses does not depend upon the illuminant. The conditions under which this is possible are given and an illustrative calculation is performed. In biological systems, where the sensor responsivities are fixed, it is shown that some changes in the illumination cause no change in the sensor responses. Such changes in illuminant are called black illuminants. It is possible to express any illuminant as the sum of two unique components. One component is a black illuminant. The second component is called the visible component. The visible component of an illuminant completely characterizes the effect of the illuminant on the vector of sensor responses.
Three range-measuring lasers arranged in triangle measure location of point. Set of three measurements of distances (ranges) of retroreflector on object from three rangefinders provides sufficient information to calculate coordinates of retroreflector in coordinate system defined by rangefinders. If at least three noncollinear retroreflectors attached to object, orientation of object also determined. Potential applications include observation and control of large structures, robotics, and machine vision.
Initial studies of the technical feasibility of using machine vision and color image processing to measure plant health were performed. Wheat plants were grown in nutrient solutions deficient in nitrogen, potassium, and iron. An additional treatment imposed water stress on wheat plants which received a full complement of nutrients. The results for juvenile (less than 2 weeks old) wheat plants show that imaging technology can be used to detect nutrient deficiencies. The relative amount of green color in a leaf declined with increased water stress. The absolute amount of green was higher for nitrogen deficient leaves compared to the control plants. Relative greenness was lower for iron deficient leaves, but the absolute green values were higher. The data showed patterns across the leaf consistent with visual symptons. The development of additional color image processing routines to recognize these patterns would improve the performance of this sensor of plant health.
The Intensity Dependent Spread (IDS) procedure is an image-processing technique based on a model of the processing which occurs in the human visual system. IDS processing is relevant to many aspects of machine vision and image processing. For quantum limited images, it produces an ideal trade-off between spatial resolution and noise averaging, performs edge enhancement thus requiring only mean-crossing detection for the subsequent extraction of scene edges, and yields edge responses whose amplitudes are independent of scene illumination, depending only upon the ratio of the reflectance on the two sides of the edge. These properties suggest that the IDS process may provide significant bandwidth reduction while losing only minimal scene information when used as a preprocessor at or near the image plane.
The papers presented at the 1990 Goddard Conference on Space Applications of Artificial Intelligence are given. The purpose of this annual conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed. The proceedings fall into the following areas: Planning and Scheduling, Fault Monitoring/Diagnosis, Image Processing and Machine Vision, Robotics/Intelligent Control, Development Methodologies, Information Management, and Knowledge Acquisition.
There has been a long standing interest in the design of controllers for multilegged vehicles. The approach is to apply distributed control to this problem, rather than using parallel computing of a centralized algorithm. Researchers describe a distributed neural network controller for hexapod locomotion which is based on the neural control of locomotion in insects. The model considers the simplified kinematics with two degrees of freedom per leg, but the model includes the static stability constraint. Through simulation, it is demonstrated that this controller can generate a continuous range of statically stable gaits at different speeds by varying a single control parameter. In addition, the controller is extremely robust, and can continue the function even after several of its elements have been disabled. Researchers are building a small hexapod robot whose locomotion will be controlled by this network. Researchers intend to extend their model to the dynamic control of legs with more than two degrees of freedom by using data on the control of multisegmented insect legs. Another immediate application of this neural control approach is also exhibited in biology: the escape reflex. Advanced robots are being equipped with tactile sensing and machine vision so that the sensory inputs to the robot controller are vast and complex. Neural networks are ideal for a lower level safety reflex controller because of their extremely fast response time. The combination of robotics, computer modeling, and neurobiology has been remarkably fruitful, and is likely to lead to deeper insights into the problems of real time sensorimotor control.
The Space Station Freedom workstation system is a distributed network of computer based workstations that provides the man-machine interfaces for controlling space station systems. This includes control of external manipulator, robotic and free flyer devices by crewmembers in the space station's pressurized shirt-sleeve environment. These remotely controlled devices help minimize the requirement for costly crew extravehicular activity (EVA) time for such tasks as station assembly and payload support. Direct window views may be used for controlling some of the systems, but many activities will be remote or require levels of detail not possible by direct observation. Since controlling remote devices becomes more difficult when direct views are inadequate or unavailable, many performance enhancing techniques have been considered for representing information about remote activities to the operator. Described here are the telepresence techniques under consideration to support operations and training. This includes video enhancements (e.g., graphic and text overlays and stereo viewing), machine vision systems, remote activity animation, and force reflection representation.
To prepare for the problem of accidents in Space Station activities, the Extravehicular Activity Retriever (EVAR) robot is being constructed, whose purpose is to retrieve astronauts and tools that float free of the Space Station. Advanced Decision Systems is at the beginning of a project to develop research software capable of guiding EVAR through the retrieval process. This involves addressing problems in machine vision, dexterous manipulation, real time construction of programs via speech input, and reactive execution of plans despite the mishaps and unexpected conditions that arise in uncontrolled domains. The problem analysis phase of this work is presented. An EVAR scenario is used to elucidate major domain and technical problems. An overview of the technical approach to prototyping an EVAR system is also presented.
The purpose of this annual conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed. The papers in this proceeding fall into the following areas: Planning and scheduling, fault monitoring/diagnosis/recovery, machine vision, robotics, system development, information management, knowledge acquisition and representation, distributed systems, tools, neural networks, and miscellaneous applications.
The papers presented at the 1990 Goddard Conference on Space Applications of Artificial Intelligence are given. The purpose of this annual conference is to provide a forum in which current research and development directed at space applications of artificial intelligence can be presented and discussed. The proceedings fall into the following areas: Planning and Scheduling, Fault Monitoring/Diagnosis, Image Processing and Machine Vision, Robotics/Intelligent Control, Development Methodologies, Information Management, and Knowledge Acquisition.
Machine vision system being developed for use in aligning ends of two round ducts before welding ends together and inspecting welded ducts for alignment after welding. System makes consistent, objective measurements quickly. Improves quality and reliability of welds, reduces need for rework, and reduces alignment and inspection time, thereby reducing cost of manufacture.
Semiautonomous rover vehicle serves as testbed for evaluation of navigation and obstacle-avoidance techniques. Designed to traverse variety of terrains. Concepts developed applicable to robots for service in dangerous environments as well as to robots for exploration of remote planets. Called Robby, vehicle 4 m long and 2 m wide, with six 1-m-diameter wheels. Mass of 1,200 kg and surmounts obstacles as large as 1 1/2 m. Optimized for development of machine-vision-based strategies and equipped with complement of vision and direction sensors and image-processing computers. Front and rear cabs steer and roll with respect to centerline of vehicle. Vehicle also pivots about central axle, so wheels comply with almost any terrain.
A relatively simple, modular, low mass, low cost robot is being developed for space EVA that is large enough to be independently mobile on a space station or platform exterior, yet versatile enough to accomplish many vital tasks. The robot comprises two long flexible links connected by a rotary joint, with 2-DOF 'wrist' joints and grippers at each end. It walks by gripping pre-positioned attachment points, such as trusswork nodes, and alternately shifting its base of support from one foot (gripper) to the other. The robot can perform useful tasks such as visual inspection, material transport, and light assembly by manipulating objects with one gripper, while stabilizing itself with the other. At SOAR '90, we reported development of 1/3 scale robot hardware, modular trusswork to serve as a locomotion substrate, and a gravity compensation system to allow laboratory tests of locomotion strategies on the horizontal face of the trusswork. In this paper, we report on project progress including the development of: (1) adaptive control for automatic adjustment to loads; (2) enhanced manipulation capabilities; (3) machine vision, including the use of neural nets, to guide autonomous locomotion; (4) locomotion between orthogonal trusswork faces; and (5) improved facilities for gravity compensation and telerobotic control.
Automated Rendezvous and Capture (AR&C) requires the determination of the six degrees of freedom relating two free bodies. Sensor systems that can provide such information have varying sizes, weights, power requirements, complexities and accuracies. One type of sensor system which can provide several key advantages is an image based tracking system, or better known as a machine vision system. By image based tracking we mean that the sensor is some imaging device such as one or more video cameras, from which the tracking parameters necessary to support the rendezvous and capture operations (range, attitude, etc.) can be derived. Image based tracking offers many advantages such as relative hardware simplicity and reprogrammability. These advantages must be weighed against the disadvantages of these systems, such as limited operational range, poorer accuracy at greater distances and sensitivity to lighting conditions. However, with properly designed algorithms and targets these disadvantages can be minimized for many important applications. Rigorous testing in realistic environments can further increase the robustness and reliability of these systems. This presentation describes the facilities used at JSC to support AR&C image based tracking development and the details of our binocular stereo approach to image based tracking.
A significant emphasis upon automation within the Space Biology Initiative hardware appears justified in order to conserve crew labor and crew training effort. Two generic forms of automation were identified: automation of data and information handling and decision making, and the automation of material handling, transfer, and processing. The use of automatic data acquisition, expert systems, robots, and machine vision will increase the volume of experiments and quality of results. The automation described may also influence efforts to miniaturize and modularize the large array of SBI hardware identified to date. The cost and benefit model developed appears to be a useful guideline for SBI equipment specifiers and designers. Additional refinements would enhance the validity of the model. Two NASA automation pilot programs, 'The Principal Investigator in a Box' and 'Rack Mounted Robots' were investigated and found to be quite appropriate for adaptation to the SBI program. There are other in-house NASA efforts that provide technology that may be appropriate for the SBI program. Important data is believed to exist in advanced medical labs throughout the U.S., Japan, and Europe. The information and data processing in medical analysis equipment is highly automated and future trends reveal continued progress in this area. However, automation of material handling and processing has progressed in a limited manner because the medical labs are not affected by the power and space constraints that Space Station medical equipment is faced with. Therefore, NASA's major emphasis in automation will require a lead effort in the automation of material handling to achieve optimal crew utilization.